PROJECT SUMMARY Metabolic perturbation or reprogramming is considered one of the hallmarks of cancer. Several common metabolic disorders, such as obesity, type 2 diabetes, and dyslipidemia, have been linked to colorectal cancer (CRC) risk. With the advances in the techniques of metabolomics, hundreds to thousands of metabolites can be systematically measured in an agnostic manner. For a well-designed prospective metabolomic study of cancer, the identification of novel risk-associated biomarkers will shed new lights on the cancer etiology and related biological pathways. Conventional studies evaluating metabolites are costly and may suffer from biases commonly encountered in the observational studies. It has been increasingly recognized that genetic factors play a significant role in determining the levels of many metabolites. Herein, I propose a cost-efficient approach to systematically evaluate the associations between plasma levels of metabolites and CRC risk. I also incorporate didactic training on molecular/genetic epidemiology, causal inference, cancer biology and metabolism, and population genetics in this application to accomplish my research and career goals described below. The proposed research is composed of four aims. In aim 1, I will build models to predict metabolite levels using existing metabolomics and high-density genotyping data from a public database and possible data generated at Vanderbilt. In aim 2, metabolites with satisfactory prediction accuracy and meeting other criteria will be evaluated in three large-scale CRC consortia with a combined sample size of ~80,900 cases and 115,000 controls to assess the associations of genetically predicted metabolite levels with CRC risk. In collaboration with other investigators during the R00 phase of this award, I will then conduct a nested case- control study to confirm up to ten metabolites identified from in silico analysis by direct measurement of these metabolites using pre-diagnosis plasma collected in three large cohort studies (aim 3). Finally, I will evaluate the potential mediation effects of metabolites for the associations between lifestyle factors including obesity (body mass index and waist-hip-ratio), physical activity, red meat intakes, vegetable intakes, healthy eating index and CRC risk (aim 4). This innovative study will, for the first time, systematically search for novel metabolite biomarkers for CRC risk using genetic instruments and validate the identified associations by direct measurement. In addition, this study will expand the understanding of underlying mechanisms causing CRC. The proposed career development award will help me building advanced knowledge of genetic and molecular epidemiology, cancer metabolism, and CRC etiology and risk assessment to transition to a successful independent investigator.